Konferenzbeitrag
Large scale GMO cultivation assessment: Tools for monitoring and modelling potential GMO impacts
Vorschaubild nicht verfügbar
Volltext URI
Dokumententyp
Text/Conference Paper
Zusatzinformation
Datum
2011
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Verlag
Shaker Verlag
Zusammenfassung
Laboratory development and field testing of genetically modified organisms (GMO) precede admission and commercial use. When entering agricultural application, implications on landscape level and regional level become more relevant. However, approaches to assess large-scale effects are still discussed in science, administration, and in agricultural management. To a relevant extent it is still open, how effects of large scale effects can be reasonably considered in risk analysis during the approval procedure, and efficiently be monitored during commercial use of GMO. Hence, the joint research project “GeneRisk” – funded by the German Federal Ministry of Education and Research – investigated systemic risks which could emerge in the course of large-scale cultivation of GMO. One central issue was to develop a web-based geographical information system (WebGIS) to analyse the feasibility of coexistence regulations with conventional / organic agriculture and exposition intensity of areas reserved for nature conservation. The software architecture was entirely based on Open Source software: The Apache webserver handles client-server communication, geodata were stored in the database management system PostgreSQL, and mapping of geodata was realised by using the Mapbender Client Suite. Since in Germany no nationwide dataset on field geometries and cultivation patterns are available, additionally, a remote sensing algorithm was developed to detect maize fields by classifying images from two satellites: 1) IRS P6 LISS-III (multispectral, 20 x 20 m²) distributed by EUROMAP, and 2) RapidEye (multispectral, 5x5 m²). The classification results for three federal states differing in field geometries and cultivation densities were evaluated using ground truth data and census data on district scale provided by the Federal Statistical Office in Germany. Based on these data on the spatial distribution of maize fields, the potential hybridisation rates were calculated using the software “MaMo” which was developed in the course of the “GeneRisk” project. Different cultivation scenarios were applied simulating both different shares of GM maize and conventional maize fields and different isolation distances separating GMO and conventional maize cultivation. The model applications revealed that even small shares of 10 % GM maize fields in some regions may result in relevant contamination rates at conventional maize. Above a labelling threshold of 0.9 % conventional harvests must be labelled as GM maize. The calculations showed that hybridisation rates depend on both the number and size of source and receptor fields and isolation distances defined for coexistence of GM and conventional maize fields. As a preliminary result it was substantiated, that in regions with high cultivation density and small field sizes the isolation distance of 150 m as set in the cultivation best practice guidelines would not be efficient to prevent gene flow above the labelling threshold.